A warm-up method for a machine system including a machine component and a machine sensor configured to sense temperature of the machine component is provided. The method comprises steps of; A) activating the machine component to execute a warm-up operation for warming up the machine component; B) determining whether the machine component is warmed up based on a target temperature corresponding to the machine component and a temperature of the machine component that is currently sensed by the machine sensor; and C) when it is determined that the machine component is warmed up, making the machine component not execute the warm-up operation.

A thermal displacement correction method is provided, including a first step of setting an initial tool temperature, a second step of estimating a temperature of a tool or a position measurement sensor based on the initial tool temperature and a temperature of a spindle, a third step of estimating an amount of thermal displacement of the tool or the position measurement sensor with a preliminarily set tool thermal displacement estimation formula based on the estimated temperature, and a fourth step of moving a feed shaft of the machine tool based on the estimated amount of thermal displacement to perform a correction. In the second step, the temperature of the spindle is measured, then a tool-mounted portion temperature of the spindle is estimated from the measured temperature.

Provided is a thermal displacement correction method using a machine learning method but making it possible to, on a user side, calculate a thermal displacement amount appropriate to a machine tool of the user and correct the thermal displacement. In a machine tool on a target user side, a thermal displacement amount between workpiece and tool corresponding to a temperature at a preset measurement point is calculated based on a parameter defining a relation between the temperature and the thermal displacement amount, and a positioning position for workpiece and tool is corrected in accordance with the calculated thermal displacement amount. On a manufacturer side, operational status information of the machine tool on the target user side is obtained, an operational status identical to the obtained operational status on the target user side is reproduced with a machine tool of a same type as the machine tool on the target user side based on the obtained operational status information, a temperature at a measurement point identical to the measurement point on the machine tool on the target user side and a thermal displacement amount between workpiece and tool are measured during reproduction, and the parameter is calculated by machine learning based on the measured temperature and thermal displacement amount. The parameter in the machine tool on the target user side is updated with the calculated parameter.

A method for operating a numerically controlled production machine includes defining a permissible value range determined by the design and construction of the production machine in which, in a normal operation during production of a workpiece, values representing a mechanical or electrical load described by acceleration and/or jolting of at least one component of the numerically controlled production machine are variable, and activating, for producing the workpiece, with a control signal a conservation operation for reducing the mechanical or electrical loads, wherein in the conservation operation the values of acceleration and/or jolting of the at least one component are variable within a part value range that is limited in comparison to the permissible value range.

A managing apparatus includes a data collecting unit that collects at least quality information on a workpiece having been machined by a first machine tool and operational information on other machine, an analyzing unit that performs an analysis for determining correlation between the quality information on a workpiece having been machined by the first machine tool and a change in the operational information on the other machine, an operation plan making unit that makes an operation plan, based on the correlation determined by the analyzing unit, for imposing a restriction on an operation of the other machine to reduce a change in environmental temperature of the first machine tool during high-precision machining performed by the first machine tool, and an operation instruction providing unit that provides an operation instruction to the other machine based on the operation plan made by the operation plan making unit.

A machine tool system is equipped with a machine tool and a controller. The machine tool is equipped with a machine tool body and at least one temperature sensor that acquires temperature data of the machine tool body. The controller is equipped with a storage that stores the temperature data acquired in time-series by the temperature sensor, and an auxiliary power supply that supplies power to the temperature sensor and the storage when the supply of power to the machine tool body is stopped. The controller controls the machine tool by using the temperature data over a predetermined time range stored in the storage, and selects, in response to a charge state of the auxiliary power supply, the temperature data to be used in first control after the supply of power to the machine tool body is resumed.

Provided is a thermal displacement correction method using a machine learning method but making it possible to, on a user side, calculate a thermal displacement amount appropriate to a machine tool of the user and correct the thermal displacement. In a machine tool on a target user side, a thermal displacement amount between workpiece and tool corresponding to a temperature at a preset measurement point is calculated based on a parameter defining a relation between the temperature and the thermal displacement amount, and a positioning position for workpiece and tool is corrected in accordance with the calculated thermal displacement amount. On a manufacturer side, operational status information of the machine tool on the target user side is obtained, an operational status identical to the obtained operational status on the target user side is reproduced with a machine tool of a same type as the machine tool on the target user side based on the obtained operational status information, a temperature at a measurement point identical to the measurement point on the machine tool on the target user side and a thermal displacement amount between workpiece and tool are measured during reproduction, and the parameter is calculated by machine learning based on the measured temperature and thermal displacement amount. The parameter in the machine tool on the target user side is updated with the calculated parameter.

A rotating tool according to an aspect of the present disclosure is a rotating tool used in a state held by a tool holder, and the rotating tool includes a shaft portion having an end attached to the tool holder, a blade attaching portion or a blade portion provided at an end of the shaft portion opposite to the end, and a plurality of sensors attached to the shaft portion, and the plurality of sensors include an acceleration sensor and a strain sensor.

An environmental temperature change prediction device includes an environmental temperature acquisition unit, an outside temperature acquisition unit, a plant environment pattern setting unit, a prediction model generating unit, and an environmental temperature change prediction unit. The environmental temperature acquisition unit measures a machine body temperature. The plant environment pattern setting unit defines in advance a classification rule for classifying change trends of the environmental temperature into a plurality of patterns based on data of the environmental temperature and the plant outside temperature and environmental temperature prediction models. The prediction model generating unit selects the applicable plant environment pattern and determines a parameter of the environmental temperature prediction model corresponding to the selected plant environment pattern. The environmental temperature change prediction unit predicts a change in the environmental temperature in a future by the environmental temperature prediction model generated in the prediction model generating unit.

To provide a reference temperature setting device, a reference temperature setting method, and a reference temperature setting program capable of setting an appropriate reference temperature for thermal displacement compensation. A reference temperature setting device comprises: an acquisition unit that acquires measured values from multiple temperature sensors installed on a machine; and a determination unit that determines setting timing for a reference temperature for thermal displacement compensation to coincide with a point in time when the measured values satisfy a predetermined condition.